Remacemide versus carbamazepine in newly diagnosed epilepsy.
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Biomedical subjects
Publications and source records attributed to John Whitehead.
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A procedure is described in which patients are randomized between two experimental treatments and a control. At a series of interim analyses, each experimental treatment is compared with control. One of the experimental treatments might then be found sufficiently superior to the control for it to be declared the best treatment, and the trial stopped. Alternatively, experimental treatments might be eliminated from further consideration at any stage. It is shown how the procedure can be conducted while controlling overall error probabilities. Data concerning evaluation of different doses of riluzole in the treatment of motor neurone disease are used for illustration.
In this paper, Bayesian decision procedures are developed for dose-escalation studies based on binary measures of undesirable events and continuous measures of therapeutic benefit. The methods generalize earlier approaches where undesirable events and therapeutic benefit are both binary. A logistic regression model is used to model the binary responses, while a linear regression model is used to model the continuous responses. Prior distributions for the unknown model parameters are suggested. A gain function is discussed and an optional safety constraint is included.